- A
Schema drift
Schema drift involves changes in the schema, such as data type mismatches, new or missing columns.
- B
Concept drift
Why wrong: Concept drift is a change in the relationship between features and the target variable, not in the input data structure.
- C
Statistical drift
Why wrong: Statistical drift involves changes in the distribution (e.g., mean, variance) of feature values, not their data types.
- D
Bias drift
Why wrong: Bias drift refers to changes in fairness metrics, not data types.
Question 31 of 1,000
MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
This MLA-C01 practice question tests your understanding of ml solution monitoring, maintenance, and security. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company uses SageMaker Model Monitor for data quality. They notice that monitoring jobs are failing intermittently with constraint violations. Upon review, they see that some features have different data types in production compared to the baseline (e.g., string instead of integer). Which type of drift is this?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Schema drift
Option A is correct because schema drift occurs when the structure or data types of features in production data differ from the baseline used during model training. In this scenario, a feature that was an integer in the baseline is now a string in production, which is a classic example of schema drift. SageMaker Model Monitor detects this by comparing the inferred schema of production data against the baseline schema, flagging any type mismatches as constraint violations.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Schema drift
Why this is correct
Schema drift involves changes in the schema, such as data type mismatches, new or missing columns.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Concept drift
Why it's wrong here
Concept drift is a change in the relationship between features and the target variable, not in the input data structure.
- ✗
Statistical drift
Why it's wrong here
Statistical drift involves changes in the distribution (e.g., mean, variance) of feature values, not their data types.
- ✗
Bias drift
Why it's wrong here
Bias drift refers to changes in fairness metrics, not data types.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse schema drift with statistical drift, thinking any change in feature values qualifies as statistical drift, but the key differentiator is that schema drift specifically involves changes in data type or structure, not just distributional shifts.
Detailed technical explanation
How to think about this question
Under the hood, SageMaker Model Monitor uses a baseline statistics and constraints file generated from training data; the constraints file includes an inferred schema with expected data types (e.g., integer, float, string). When a monitoring job runs, it parses production data and compares each feature's type against the baseline; a mismatch triggers a constraint violation and can cause the job to fail. In real-world scenarios, schema drift often arises from upstream data pipeline changes, such as a source system switching from numeric IDs to alphanumeric strings, which can silently break model inference if not caught.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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ML Solution Monitoring, Maintenance, and Security — study guide chapter
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
ML Solution Monitoring, Maintenance, and Security — This question tests ML Solution Monitoring, Maintenance, and Security — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Schema drift — Option A is correct because schema drift occurs when the structure or data types of features in production data differ from the baseline used during model training. In this scenario, a feature that was an integer in the baseline is now a string in production, which is a classic example of schema drift. SageMaker Model Monitor detects this by comparing the inferred schema of production data against the baseline schema, flagging any type mismatches as constraint violations.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
This MLA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLA-C01 exam.
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